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nicoloceneda

Fred St Louis MCP

by nicoloceneda
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Python
Remote

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    Related Servers

    • fred

      pipeworx-io
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables querying Federal Reserve Economic Data (FRED) via tools for searching series, retrieving series metadata, and fetching time series observations, covering over 800,000 economic indicators.
      6 npm
      MIT

    • FRED API MCP Server

      dracepj
      F
      license
      A
      quality
      D
      maintenance
      Enables searching and retrieving economic data from the Federal Reserve Economic Data (FRED) API, including time series, categories, releases, and popular indicators.
      7
      1
      -

    • fred-mcp

      fritzprix
      A
      license
      A
      quality
      D
      maintenance
      Enables users to search, retrieve, and explore economic data series from the Federal Reserve Economic Data (FRED) API using natural language.
      11
      MIT

    • insightiq-mcp

      ravi-p-k-1
      A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to search the live FRED series catalog and retrieve historical economic observations so they can answer economic questions with real Federal Reserve data.
      1
      Creative Commons Zero v1.0 Universal

    • FRED Economic MCP Server

      satendra-mani-tiwari
      A
      license
      Not graded
      quality
      D
      maintenance
      Provides access to 800,000+ Federal Reserve Economic Data (FRED) time series, enabling users to search, retrieve, and analyze economic indicators like GDP, unemployment, inflation, and interest rates through natural language queries.
      MIT

    • fred-mcp

      mcpwright
      A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to search and retrieve FRED economic time series, including vintage (as-published) data, with tools for series search, observation retrieval, release calendar, revision history, and more.
      9
      33 PyPI
      MIT
    Deploy Server
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    TDQS

    C2.1/5.0

    Scored across 40 tools

    Disambiguation4/5

    Most tools have distinct purposes targeting specific FRED resources and operations, but there is some overlap between general request tools (fred_request, fred_v2_request, geofred_request) and specific endpoint tools, which could cause confusion about when to use which. The alias 'get_series_observations' duplicates 'get_observations', adding minor redundancy.

    Naming Consistency5/5

    Tool names follow a highly consistent verb_noun pattern (e.g., get_category, search_series, get_release_dates) with clear snake_case throughout. The three general request tools (fred_request, fred_v2_request, geofred_request) deviate slightly but maintain a predictable naming style.

    Tool Count2/5

    With 40 tools, the count is excessive for the FRED API domain, making the surface overwhelming and likely to confuse agents. A more focused set of 10-20 tools covering core operations would be more appropriate, as many tools are highly specific (e.g., get_category_related_tags, get_release_tables) that could be consolidated.

    Completeness5/5

    The tool set provides comprehensive coverage of the FRED API domain, including categories, series, releases, sources, tags, and geospatial data, with full CRUD-like operations (mostly GET/search) and no apparent gaps. It supports all major workflows for economic data retrieval and analysis.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources